The chambers in a cluster tool are expensive resources that are wasted if allowed to sit idle. Thus, whenever possible, an operator will attempt to optimize the use of the tool in terms of minimizing the amount of time it takes for a substrate lot to be processed. However, it may be difficult and time consuming to manually optimize operation of a cluster tool to process a substrate lot even when all substrates in the lot are to follow similar paths through the tool and undergo the same processing. The amount of time saved by optimizing may not always exceed the amount of time employed to optimize a tool for processing the lot. Typically, a fairly large number of substrates must be processed to realize the benefit. And, even worse, in the case where each substrate in a lot is to undergo different process steps from the other substrates, the time employed to optimize a conventional cluster tool for each set of different process steps would likely exceed the amount of time saved by optimizing. This may be true no matter how many substrates are processed since the tool may need to be reconfigured for each substrate. Therefore, what is needed are methods and systems to optimize a cluster tool such that time saved by operating while optimized is not lost by the time it takes to optimize operation of the cluster tool.